A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer
type: Item
instance of: scholarly article
title: A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer
zbMATH Open document ID: 1403.92088
author: Santiago Vilar
author: Lourdes Santana
author: Eugenio Uriarte
author: Humberto González Díaz
published in: Journal of Theoretical Biology
publication date: 2018-12-11T00:00:00Z
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 6991767
zbMATH Keywords: protein sequence
zbMATH Keywords: colorectal cancer
zbMATH Keywords: Markov chains
zbMATH Keywords: HP lattice
zbMATH Keywords: complex networks
zbMATH Keywords: biomarkers
zbMATH Keywords: QSAR
zbMATH Keywords: linear discriminant analysis
zbMATH Keywords: sequence alignment
zbMATH Keywords: electrostatic potential
Wikidata QID: Q84346859
describes a project that uses: Cell-PLoc
describes a project that uses: QuatIdent
describes a project that uses: GPCR-CA
describes a project that uses: STATISTICA
describes a project that uses: ProtIdent
describes a project that uses: FoldRate
MaRDI profile type: Publication
full work available at URL: j.jtbi.2009.07.031
OpenAlex ID: W2087137877
cites work: Predicting protein structural class based on multi-features fusion
cites work: Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
cites work: The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition
cites work: Enzymes/non-enzymes classification model complexity based on composition, sequence, 3D and topological indices
cites work: Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices
cites work: Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on auto covariance approach
DOI: 10.1016/J.JTBI.2009.07.031
description: scientific article; zbMATH DE number 6991767